Variable selection in seemingly unrelated regressions with random predictors

David Puelz, P. Richard Hahn, Carlos M. Carvalho

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


This paper considers linear model selection when the response is vectorvalued and the predictors, either all or some, are randomly observed. We propose a new approach that decouples statistical inference from the selection step in a "post-inference model summarization" strategy. We study the impact of predictor uncertainty on the model selection procedure. The method is demonstrated through an application to asset pricing.

Original languageEnglish (US)
Pages (from-to)969-989
Number of pages21
JournalBayesian Analysis
Issue number4
StatePublished - 2017
Externally publishedYes


  • Decoupling shrinkage and selection
  • Penalized utility selection
  • Seemingly unrelated regressions

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics


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